Phacomatosis pigmentovascularis type IIb associated with Sturge-Weber syndrome and pyogenic granuloma

A case of phacomatosis pigmentovascularis (PPV) in a 6-year-old girl with Sturge-Weber syndrome, pyogenic granuloma, and other complications is described. It is relatively rare that a complete form of Sturge-Weber syndrome was associated with PPV. A review of the literature on PPV, focusing on total number of reported cases and etiological speculations, is presented. To our knowledge, a total of 118 cases of PPV, including the present one, have been reported to date. Regardless of many speculations, the true etiology remains unknown. The average "density" of mast cells (MCs) per mm2 appearing in the central region of the pyogenic granuloma was calculated to be 86.3/mm2 and that in the adjacent nevus flammeus was 37.9/mm2. The "density" of mast cells in pyogenic granuloma separately calculated from ten other cases was 105.5 +/- 28.6/mm2 (mean +/- SD), compared with that in normal skin, 6.85 +/- 4.9/mm2 (n = 20). There was a significant difference between the two, indicating that MCs are closely associated with angiogenesis in pyogenic granuloma.     

Signal flow graph modelling of interleaved buck converters

This paper presents a systematic development of unified signal flow graph model for an interleaved buck converter system operating in continuous inductor current mode. From this signal flow graph small, large‐signal and steady‐state models are developed, which are useful to study the converter dynamic and steady‐state behaviour. Converter performance expressions like steady‐state voltage gain, efficiency expressions and other small‐signal characteristic transfer functions are derived. Development of unified signal flow graph is explained for a 3‐cell interleaved converter system. Derivation of large, small‐signal and steady‐state models from the unified signal flow graph is demonstrated by considering a 2‐cell interleaved buck converter system. Large signal model was programmed in TUTSIM simulator, and the large‐signal responses against supply, load disturbances were predicted. Signal flow graph analysis results are validated with PSIM simulations. Further, the mathematical models obtained from the signal flow graph modelling are in agreement with those obtained from the state‐space averaging technique. Copyright © 2003 John Wiley & Sons, Ltd.     

A hybrid power system using alternative energy facilities in isolated island

A hybrid power system uses many wind turbine generators in isolated small islands. The output power of wind turbine generators is mostly fluctuating and has an effect on system frequency. In order to solve this problem, we propose a new power system using renewable energy in small, isolated islands. The system can supply high-quality power using an aqua electrolyzer, fuel cell, renewable energy, and diesel generator. The generated hydrogen by an aqua electrolyzer is used as fuel for a fuel cell. The simulation results are given to demonstrate the availability of the proposed system in this paper.     

A novel tumor suppressor locus on chromosome 18q involved in the development of human lung cancer

The high incidence of loss of heterozygosity (LOH) on chromosome 18q in advanced non-small cell lung carcinomas indicates the presence of tumor suppressor gene(s) on this chromosome arm, which plays an important role in the acquisition of malignant phenotypes in lung cancers. In the present study, we examined 62 lung cancer specimens and 54 lung cancer cell lines for allelic imbalance at 11 microsatellite loci to define common regions of 18q deletions. Allelic imbalance of 18q was detected in 24 (55.8%) non-small cell lung carcinoma specimens and in 6 (31.6%) small cell lung carcinoma specimens, whereas a similar frequency of LOH was statistically inferred to occur in cell lines by analyzing marker homozygosity as an indirect measure of LOH. Five specimens and 11 cell lines showed partial or interstitial deletions of chromosome 18q, and 2 of them had homozygous deletions at the 18q21.1 region. A commonly deleted region was assigned between the D18S46 and y953G12R loci. The size of this region is less than 1 Mb, and the coding exons of three candidate tumor suppressor genes, Smad2, Smad4, and DCC, were mapped outside the region. This result suggests that the common region harbors a novel tumor suppressor gene involved in the progression of lung cancer.     

Evaluation of the Anti-Proliferative Activity of Rare Aldohexoses against MOLT-4F and DU-145 Human Cancer Cell Line and Structure-Activity Relationship of D-Idose

D-Allose (D-All), a C-3 epimer of D-glucose (D-Glc), is a naturally rare monosaccharide, which shows anti-proliferative activity against several human cancer cell lines. Unlike conventional anticancer drugs, D-All targets glucose metabolism and is non-toxic to normal cells. Therefore, it has attracted attention as a unique “seed” compound for anticancer agents. However, the anti-proliferative activities of the other rare aldohexoses have not been examined yet. In this study, we evaluated the anti-proliferative activity of rare aldohexoses against human leukemia MOLT-4F and human prostate cancer DU-145 cell lines. We found that D-All and D-idose (D-Ido) at 5 mM inhibited cell proliferation of MOLT-4F cells by 46 % and 60 %, respectively. On the other hand, the rare aldohexoses at 5 mM did not show specific anti-proliferative activity against DU-145 cells. To explore the structure–activity relationship of D-Ido, we evaluated the anti-proliferative activity of D-sorbose (D-Sor), 6-deoxy-D-Ido, and L-xylose (L-Xyl) against MOLT-4F cells and found that D-Sor, 6-deoxy-D-Ido, and L-Xyl showed no inhibitory activity at 5 mM, suggesting that the aldose structure and the C-6 hydroxy group of D-Ido are important for its activity. Cellular glucose uptake assay and western blotting analysis of thioredoxin-interacting protein (TXNIP) expression suggested that the anti-proliferative activity of D-Ido is induced by inhibition of glucose uptake via TXNIP-independent pathway.     

Signal flow graph modelling and analysis of interleaved DC?DC parallel converters

This paper presents a systematic development of a unified signal flow graph model for an interleaved DC–DC parallel converter system operating in continuous current mode. This signal flow graph approach provides a means to translate directly the switching converter to its graphic model, from which the steady-state and dynamic behaviour of the converter can be studied easily. The development of a unified signal flow graph is explained for a three-cell interleaved parallel converter system. Derivation of large-signal, small-signal and steady-state models from a unified signal flow graph is demonstrated by considering a two-cell interleaved converter system operating in complementary activation mode. Converter performance expressions such as steady-state voltage gain, efficiency expressions and small-signal characteristic transfer functions are also derived. A large-signal model was programmed in a TUTSIM simulator, and the large-signal responses against supply and load disturbances were predicted. Signal flow graph analysis results are validated with PSIM simulations. Experimental observations are provided to validate the signal flow graph modelling method. Further, the mathematical models obtained from the signal flow graph modelling are in agreement with those obtained from the state-space averaging technique.     

Next Day Peak Load Forecasting Using Neural Network With Adaptive Learning Algorithm Based On Similarity

In this article we propose the adaptive learning algorithm of neural network with respect to a rapid temperature change of forecasted day. The proposed adaptive learning algorithm is used to shift the learning range of previous year of forecasted day. Therefore, the proposed neural network can be trained by using learning data, including the maximum temperature to be forecasted. The suitability of the proposed approach is illustrated through an application to actual load data of Okinawa Electric Power Company in Japan.     

Sensorless vector control of synchronous reluctance motors withdisturbance torque observer

The elimination of the position sensor has been one important requirement in vector control systems because the position sensor spoils the reliability and simplicity of drive systems. Therefore, we present a sensorless vector control technique for synchronous reluctance motors. The rotor position is calculated easily from ds-qs-axes flux linkages which are estimated with a first-order lag compensator. Furthermore, utilizing estimated rotor position as the input of the full-order observer, the rotor speed and disturbance torque are estimated. The proposed sensorless vector control scheme is demonstrated with experimental results     

Particle swarm optimization with genetic recombination: a hybrid evolutionary algorithm

This article presents a hybrid evolutionary algorithm (HEA) based on particle swarm optimization (PSO) and a real-coded genetic algorithm (GA). In the HEA, PSO is used to update the solution, and a genetic recombination operator is added to produce offspring individuals based on the parents, which are selected in proportion to their relative fitness. Through the recombination, new offspring enter the population, and individuals with poor fitness are eliminated. The performance of the proposed hybrid algorithm is compared with those of the original PSO and GA, and the impact of the recombination probability on the performance of the HEA is also analyzed. Various simulations of multivariable functions and neural network optimizations are carried out, showing that the proposed approach gives a superior performance to the canonical means, as well as a good balance between exploration and exploitation.     

Intelligent control of a three-DOF planar underactuated manipulator

Recently, computational intelligence has been applied extensively in control engineering, especially for systems that cannot easily be controlled by conventional means. In this article, attention is paid to the control of a three-DOF planar underactuated manipulator, also known as the three-link gymnastic robot, by utilizing a neural network (NN) and a genetic algorithm (GA). In an attempt to make the problem more analogous to human gymnastics, constraints are applied to the joint angles. With different swing-up timings, the performance of the proposed controller is investigated and control simulations are performed. Numerical simulations show that the neurocontroller is able to control the system effectively within the constraints and given timings.